Patients with advanced cancers receiving a multidrug combination matched to a higher number of genomic alterations had improved disease control rates (DCR), progression-free survival (PFS) and overall survival (OS) compared with patients receiving therapy matched to fewer genomic alterations, according to a study published in Nature Medicine

Precision medicine clinical trials in oncology often involve matching specific tumor genomic characteristics of patients with refractory advanced cancers to specific therapies that are targeted to those molecular alterations.  Although multiple potentially pathogenic genomic alterations are common in individual patients with advanced cancers, many of these studies involve single-agent therapy matched to only 1 genomic alteration. 

The Investigation of Profile-Related Evidence Determining Individualized Cancer Therapy (I-PREDICT) study (ClinicalTrials.gov Identifier: NCT02534675), a prospective, open-label navigation trial conducted at the University of California, San Diego, La Jolla, California, and Avera Cancer Institute, Sioux Falls, South Dakota, used targeted exome sequencing to interrogate the tumor genomes of patients with a variety of advanced cancers in order to determine the status of 236 to 405 genes, and, in some cases, the tumor mutational burden (TMB) and microsatellite status of the tumor. In addition, immunohistochemical evaluation of programmed cell death-ligand 1, and sequencing of circulating tumor DNA were also performed, when possible.

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Of the 149 patients with refractory metastatic cancers enrolled in the study, approximately 60% were diagnosed with advanced gastrointestinal, hepatopancreatobiliary, or gynecologic cancers, the median number of prior therapies administered in the metastatic setting was 2, and the median number of characterized genomic alterations was 5.

Patient cases and corresponding molecular data were examined in the context of a molecular tumor board (MTB) made up of oncologists, pharmacologists, cancer biologists, geneticists, surgeons, radiologists, pathologists, and bioinformatics experts who provided treatment recommendations. Eighty-three (55.7%) of these patients received treatment and were included in this analysis.

For patients in this subgroup, a “matching score” was determined, defined as the number of molecular alterations matched to the drugs administered divided by the total number of characterized genomic alterations, with scores higher than 50% and at 50% or lower defined as high and low matching scores, respectively. Of the 83 patients receiving treatment, 73 patients (88%) received 1 or more matched treatments.

With a median follow-up of 10.8 months, key findings for the subgroup of 83 patients include a significantly higher disease control rate in patients with a high vs low matching score (50% vs 22.4%; P =.028). Furthermore, on multivariate analyses, a high matching score was found to be an independent predictor of DCR (odds ratio [OR], 3.6; 95% CI, 1.1–11.8; P =.033), PFS (hazard ratio [HR], 0.34; 95% CI, 0.19–0.62; P =.0004), and OS (HR, 0.42; 95% CI, 0.18–0.95; P =.038) compared with a low matching score.

Another interesting result was that patients with a matching score of higher than 50% were more likely to achieve a PFS duration ratio of current treatment to immediately prior treatment of 1.3 or more therapies compared with those with a low matching score (ie, 75% vs 36.6%; P =.026 on multivariate analysis), suggesting that the matched treatment regimen was associated with improved clinical outcome compared with the treatment administered immediately before the matched therapy.  

In the subgroup of 83 patients, 19.3% experienced at least 1 serious adverse event, including 19.2% and 20% with or without 1 or more matched treatments, respectively. No treatment-related deaths occurred.  

Study limitations noted by the authors included the absence of a control group, the potential for different numbers of genomic alterations to be identified using different sequencing panels, thereby affecting cutoff values for matching, and the fact that matches related to TMB may confound matching cutoff values derived using only specific gene targets and the agents targeted to them.

In their concluding remarks, the study authors noted that “taken together, our findings underscore the safety, feasibility, and importance of designing precision oncology trials that emphasize personalized, individually tailored combination therapies, rather than scripted monotherapies, for patients with lethal cancers. Follow-up studies with greater numbers of patients are needed to confirm our findings.”

Reference

Sicklick, JK, Kato S, Okamura R, et al. Molecular profiling of cancer patients enables personalized combination therapy: the I-PREDICT study [published online April 22, 2019]. Nature Med.  doi: 10.1038/s41591-019-0407-5